Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation

Abstract

Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems in AnyLogic™ to create digital shadows as the first step towards a full digital twin. The generic simulation visualises production systems automatically and displays key performance indicators (KPIs) for the planned production program, using representational state transfer (REST) interfaces to extract product and production data from an ERP system. The case study has been applied in a learning factory of the University of Applied Life Sciences Emden/Leer. The results prove the presented concept of the generic simulation and show the limits and challenges of working with generic simulation models.

DES and IIoT fusion approach towards real-time synchronization of physical and digital components in manufacturing processes

“…The suggested framework comprised numerous pieces of software that provided layout and control logic information for the modeled items. According to this technique, the layout and control logic of the manufacturing system must be designed with suitable software (Kassen et al, 2021).…”

Digitale Zwillinge in der Bioprozesstechnik – Chancen und Möglichkeiten

“…[26,34,35] Der Begriff des digitalen Zwillings wird in der Literatur ebenfalls unterschiedlich genutzt. So wird ein DZ in seiner urspru ¨nglichen Idee, begru ¨ndet von Grieves et al [36] in den fru ¨hen 2000er-Jahren, sehr vereinfacht als virtuelles System verstanden, das alle Informationen und Daten seiner physischen Spiegelung entha ¨lt [37,38]. Damit entspricht diese a ¨ltere Definition heutzutage eher der Definition eines digitalen Schattens.…”

“…Eine weiterfu ¨hrende Definition bot um 2012 die NASA. Sie beschrieb digitale Zwillinge als hochentwickelte, multiphysikalische Modelle und Simulationen, die u ¨ber sa ¨mtliche zu messenden sensorischen Daten mit dem realen Objekt verbunden sind [25,29,34,[37][38][39][40]. Aber auch diese Definition ist aus heutiger Sicht nicht mehr zufriedenstellend.…”

Retrofitting-Based Development of Brownfield Industry 4.0 and Industry 5.0 Solutions

“…• Did not describe the use case and deployed technologies explicitly [40], [41] • Conduct the retrofitting work without I4.0 orientation [42] • Performed the validation in a fragmented way, not related to any industrial machinery [43]- [45]. Only for the cyber-security aspect, we accept research papers in this section that have the experiments conducted without specific machinery but simulation scenarios, considering the special characteristics of this aspect and its scarcity of research work.…”